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# Machine Learning Engineer

- **Company:** Somatus, Inc.
- **Location:** McLean, VA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, JIRA, Microsoft Azure, Cloud Computing, Relational Databases, Linux, Monitoring of Systems, Issue Tracking Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Software Construction, Software Engineering, Feature Engineering, Delivery Pipeline, Model Validation, Git, Data Analytics, Machine Learning Operations, Docker
- **Published:** July 8, 2026
- **Apply:** https://dejobs.org/x/x/2FDFD3214186487FA0C0BDE8F444CC09/job/

## About the Role

* Bachelor's or Master's Degree with 1 or more years of experience in a machine learning-related role, or PhD
 * At least 1 year of experience with Python
 * Some experience with relational databases and SQL
 * Understanding of software engineering best practices and software development lifecycle
 * Familiarity with Git and issue tracking tools such as JIRA
 * Familiarity with Linux and CLI, * Experience in healthcare industry and working with healthcare data
 * Experience with cloud infrastructure (Azure, AWS, or GCP)
 * Experience with Docker
 * Experience with Natural Language Processing
 * Experience with effectiveness research

## Description

Somatus is on a mission to be the world's best provider of integrated care for patients with or at risk of developing kidney disease. A core component of our mission is the effective and impactful use of data to support patient care. As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems. Our culture is data-driven, collaborative, results-focused, and fast-moving.

If you have a passion for building things and using data to impact the lives of patients, families, and communities, then we want to speak with you!

 * Partner with ML engineers, data engineers, software developers, product managers, data analysts, and clinical and operations team members to deliver machine learning solutions that make an impact.
 * Assist with end-to-end lifecycle for AI and machine learning projects, including idea generation, data and feature engineering, model training, model evaluation, model testing, model deployment, model monitoring, and maintenance.
 * Build pipelines for training, evaluating, and deploying models.
 * Perform exploratory data analysis, statistical modeling, causal inference, and other advanced analytical techniques to uncover meaningful insights.
 * Advise stakeholders on experimentation best practices and help design and implement A/B/n testing as needed.
 * Stay current with trends and developments in the AI, machine learning, and healthcare technology communities.


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